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Read logs

get_logs
Read-only

Logs. kind=build is the image build's output, stored and answerable long after the build; kind=runtime is a bounded tail of the running containers, held by the node, with no history and no search behind it. For kind=runtime, service narrows the tail to one service of the project — without it every service is interleaved, which on a project with more than one is most of what you read. The names are the ones get_project_detail lists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
linesNo
serviceNo
project_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish readOnlyHint=true and openWorldHint=false, so the description is free to add the non-obvious traits: build logs persist indefinitely while runtime logs are a bounded tail held by the node with no history and no search. That retention/searchability disclosure is exactly the kind of context an agent cannot infer from the schema. It stops short of mentioning pagination or ordering.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences with no filler; the kind distinction is front-loaded and the service caveat follows. Every clause carries semantics. Slightly harder to scan than a bulleted kind/parameter layout would be, but there is no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with no output schema, no enums, and 0% schema coverage, the description covers behavior and kind semantics well but leaves `lines` and `project_id` unexplained, and says nothing about what a returned log record looks like. Adequate but with clear gaps given the schema contributes no documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the load. It explains `kind` and `service` well, including the effect of omitting `service` on multi-service projects. However, `lines` (the tail size) and the required `project_id` are never explained, leaving two of four parameters undocumented anywhere.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The tool reads logs for a project, and the description goes further by defining the two `kind` values precisely (build output vs. running-container tail). It clearly distinguishes itself from data-listing siblings by naming get_project_detail as the source of service names. The opening 'Logs.' is terse rather than a stated verb, which keeps it short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit guidance for choosing between kind=build and kind=runtime, including the retention tradeoff ('answerable long after the build' vs. 'no history and no search'). It also states the condition that makes `service` worth passing. It does not, however, address when to prefer this tool over any other sibling for log-like information.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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